Signal representation for compression and noise reduction through frame-based wavelets

Laura Rebollo - Neira, Anthony G. Constantinides, Tania Stathaki

    Research output: Contribution to journalArticlepeer-review


    A mathematical framework for data representation and for noise reduction is presented in this paper. The basis of the approach lies in the use of wavelets derived from the general theory of frames to construct a subspace capable of representing the original signal excluding the noise. The representation subspace is shown to be efficient in signal modeling and noise reduction, but it may be accompanied by an ill-conditioned inverse problem. This is further examined, and a more adequate orthonormal representation for the generated subspace is proposed with an improvement in compression performance.
    Original languageEnglish
    Pages (from-to)587-597
    Number of pages11
    JournalIEEE Transactions on Signal Processing
    Issue number3
    Publication statusPublished - Mar 1998

    Bibliographical note

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    • data compression
    • interference suppression
    • inverse problems
    • noise
    • signal representation
    • wavelet transforms
    • data representation
    • frame-based wavelets
    • general theory of frames
    • ill-conditioned inverse problem
    • noise reduction
    • orthonormal representation
    • representation subspace
    • signal modeling
    • subspace
    • wavelets


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